Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Sep 4;18(9):2938.
doi: 10.3390/s18092938.

A Capillary Computing Architecture for Dynamic Internet of Things: Orchestration of Microservices from Edge Devices to Fog and Cloud Providers

Salman Taherizadeh  1   2 , Vlado Stankovski  3   4 , Marko Grobelnik  5
Affiliations

A Capillary Computing Architecture for Dynamic Internet of Things: Orchestration of Microservices from Edge Devices to Fog and Cloud Providers

Salman Taherizadeh et al. Sensors (Basel). .

Abstract

The adoption of advanced Internet of Things (IoT) technologies has impressively improved in recent years by placing such services at the extreme Edge of the network. There are, however, specific Quality of Service (QoS) trade-offs that must be considered, particularly in situations when workloads vary over time or when IoT devices are dynamically changing their geographic position. This article proposes an innovative capillary computing architecture, which benefits from mainstream Fog and Cloud computing approaches and relies on a set of new services, including an Edge/Fog/Cloud Monitoring System and a Capillary Container Orchestrator. All necessary Microservices are implemented as Docker containers, and their orchestration is performed from the Edge computing nodes up to Fog and Cloud servers in the geographic vicinity of moving IoT devices. A car equipped with a Motorhome Artificial Intelligence Communication Hardware (MACH) system as an Edge node connected to several Fog and Cloud computing servers was used for testing. Compared to using a fixed centralized Cloud provider, the service response time provided by our proposed capillary computing architecture was almost four times faster according to the 99th percentile value along with a significantly smaller standard deviation, which represents a high QoS.

Keywords: Edge computing; Fog computing; Internet of Things; Microservices; container-based virtualization; on/offloading.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Applications structure of monolithic versus Microservices architecture.
Figure 2
Figure 2
Onloading or offloading Microservices between different layers (Edge, Fog and Cloud) in the proposed capillary distributed computing architecture.
Figure 3
Figure 3
The proposed capillary distributed computing architecture for smart IoT applications.
Figure 4
Figure 4
Sequence diagram for an on/offloading scenario performed by the capillary computing architecture.
Figure 5
Figure 5
MACH Edge node developed in one of our ongoing projects called OPTIMUM is settled in the vehicle.
Figure 6
Figure 6
VESNA high-performance microcontroller.
Figure 7
Figure 7
Situations when aggressive left and right turns are recognized.
Figure 8
Figure 8
Situations when hard braking events are recognized.
Figure 9
Figure 9
NSR values offered by two Fog nodes in a specific part of the trip.
Figure 10
Figure 10
Service response time provided by our proposed capillary computing architecture.
Figure 11
Figure 11
Service response time provided by the unintelligent method.
Figure 12
Figure 12
CDF of response time offered by the Edge, Fog and Cloud infrastructures.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Suárez-Albela M., Fernández-Caramés T.M., Fraga-Lamas P., Castedo L. A Practical Evaluation of a High-Security Energy-Efficient Gateway for IoT Fog Computing Applications. Sensors. 2017;17:1978. doi: 10.3390/s17091978. - DOI - PMC - PubMed
    1. Song F., Ai Z., Li J., Pau G., Collotta M., You I., Zhang H. Smart Collaborative Caching for Information-Centric IoT in Fog Computing. Sensors. 2017;17:2512. doi: 10.3390/s17112512. - DOI - PMC - PubMed
    1. Taherizadeh S., Jones A., Taylor I., Zhao Z., Stankovski V. Monitoring self-adaptive applications within edge computing frameworks: A state-of-the-art review. J. Syst. Softw. 2018;136:19–38. doi: 10.1016/j.jss.2017.10.033. - DOI
    1. Raspberry Pi 3 Model B. [(accessed on 8 August 2018)]; Available online: https://www.raspberrypi.org/products/raspberry-pi-3-model-b/
    1. Arduino. [(accessed on 8 August 2018)]; Available online: https://www.arduino.cc/

LinkOut - more resources